Genome-wide discovery and validation of diagnostic DNA methylation-based biomarkers for hepatocellular cancer detection in circulating cell free DNA

Epigenetic modification in liver fibrosis: Promising therapeutic direction with significant challenges ahead

Liver fibrosis, characterized by scar tissue formation, can ultimately result in liver failure. It's a major cause of morbidity and mortality globally, often associated with chronic liver diseases like hepatitis or alcoholic and non-alcoholic fatty liver diseases. However, current treatment options are limited, highlighting the urgent need for the development of new therapies. As a reversible regulatory mechanism, epigenetic modification is implicated in many biological processes, including liver fibrosis. Exploring the epigenetic mechanisms involved in liver fibrosis could provide valuable insights into developing new treatments for chronic liver diseases, although the current evidence is still controversial. This review provides a comprehensive summary of the regulatory mechanisms and critical targets of epigenetic modifications, including DNA methylation, histone modification, and RNA modification, in liver fibrotic diseases. The potential cooperation of different epigenetic modifications in promoting fibrogenesis was also highlighted. Finally, available agonists or inhibitors regulating these epigenetic mechanisms and their potential application in preventing liver fibrosis were discussed. In summary, elucidating specific druggable epigenetic targets and developing more selective and specific candidate medicines may represent a promising approach with bright prospects for the treatment of chronic liver diseases.

Developments and current status of cell-free DNA in the early detection and management of hepatocellular carcinoma

Nowadays, hepatocellular carcinoma (HCC) is still a major threat to human health globally, with a disappointing prognosis. Regular monitoring of patients at high risk, utilizing abdominal ultrasonography combined with alpha-fetoprotein (AFP) serum analysis, enables the early detection of potentially treatable tumors. However, the approach has limitations due to its lack of sensitivity. Meanwhile, the current standard procedure for obtaining a tumor biopsy in cases of HCC is invasive and lacks the ability to assess the dynamic progression of cancer or account for tumor heterogeneity. Hence, there is a pressing need to develop non-invasive, highly sensitive biomarkers for HCC which can improve the accuracy of early diagnosis, assess treatment response and accurately predict the prognosis. In contrast to the conventional method of tissue biopsy, liquid biopsy offers a non-invasive approach that can be readily repeated. As a liquid biopsy approach, the analysis of cell-free DNA (cfDNA) offers real-time insights that can accurately portray the tumor burden and provide a comprehensive depiction of the genetic profile associated with HCC. In this review, we present a comprehensive summary of the recent research findings pertaining to the significance and potential practicality of cfDNA analysis in the early detection and effective management of HCC.

Early detection of hepatocellular carcinoma via no end-repair enzymatic methylation sequencing of cell-free DNA and pre-trained neural network

BACKGROUND

Early detection of hepatocellular carcinoma (HCC) is important in order to improve patient prognosis and survival rate. Methylation sequencing combined with neural networks to identify cell-free DNA (cfDNA) carrying aberrant methylation offers an appealing and non-invasive approach for HCC detection. However, some limitations exist in traditional methylation detection technologies and models, which may impede their performance in the read-level detection of HCC.

METHODS

We developed a low DNA damage and high-fidelity methylation detection method called No End-repair Enzymatic Methyl-seq (NEEM-seq). We further developed a read-level neural detection model called DeepTrace that can better identify HCC-derived sequencing reads through a pre-trained and fine-tuned neural network. After pre-training on 11 million reads from NEEM-seq, DeepTrace was fine-tuned using 1.2 million HCC-derived reads from tumor tissue DNA after noise reduction, and 2.7 million non-tumor reads from non-tumor cfDNA. We validated the model using data from 130 individuals with cfDNA whole-genome NEEM-seq at around 1.6X depth.

RESULTS

NEEM-seq overcomes the drawbacks of traditional enzymatic methylation sequencing methods by avoiding the introduction of unmethylation errors in cfDNA. DeepTrace outperformed other models in identifying HCC-derived reads and detecting HCC individuals. Based on the whole-genome NEEM-seq data of cfDNA, our model showed high accuracy of 96.2%, sensitivity of 93.6%, and specificity of 98.5% in the validation cohort consisting of 62 HCC patients, 48 liver disease patients, and 20 healthy individuals. In the early stage of HCC (BCLC 0/A and TNM I), the sensitivity of DeepTrace was 89.6 and 89.5% respectively, outperforming Alpha Fetoprotein (AFP) which showed much lower sensitivity in both BCLC 0/A (50.5%) and TNM I (44.7%).

CONCLUSIONS

By combining high-fidelity methylation data from NEEM-seq with the DeepTrace model, our method has great potential for HCC early detection with high sensitivity and specificity, making it potentially suitable for clinical applications. DeepTrace: https://github.com/Bamrock/DeepTrace.

Early screening of nasopharyngeal carcinoma

The low positive predictive value (PPV) of early screening of nasopharyngeal carcinoma (NPC) is the problems that need to be solved urgently. The combination of cell-free DNA (cfDNA) methylation testing and Epstein-Barr virus (EBV) serological testing is the key to solve this problem. This paper reviews recent advances in early screening for NPC and cfDNA methylation, with future perspectives. Pubmed was searched for the literature related to early screening of NPC and cfDNA methylation in the past 5 years. The results of these studies were summarized. Despite these efforts, the PPV is still low (10%). Previous studies have shown that cfDNA methylation analysis has good specificity and accuracy across a variety of tumors. The combination of cfDNA methylation and EBV detection helps to improve the PPV for early screening of NPC. The combination of cfDNA methylation and EBV serological testing is key to addressing the low PPV of NPC early screening.

Refinement and validation of a comprehensive clinical diagnostic model (GAMAD) based on gender, age, multitarget circulating tumour DNA methylation signature and commonly used serological biomarkers for early detection of hepatocellular carcinoma: a multicentre, prospective observational study protocol

INTRODUCTION

Prompt detection of hepatocellular carcinoma (HCC) in patients with chronic liver diseases is critical for enhancing prognosis. Existing imaging techniques and serum markers fall short of clinical needs. This study aims to establish a non-invasive diagnostic model for early HCC detection in the Chinese population.

METHODS AND ANALYSIS

This prospective, multicentre, observational study will enrol 2000 participants, including HCC patients, those with chronic liver diseases (hepatitis, cirrhosis and benign liver space-occupying lesions), and healthy individuals. The study will collect demographic data and blood samples, which will be used to test α-fetoprotein (AFP), des-γ-carboxy-prothrombin (DCP) and circulating tumour DNA (ctDNA) methylation. The GAMAD (Gender+Age+Methylation+AFP+DCP) model involving gender, age, ctDNA methylation signature, AFP and DCP will be developed and blindly validated in training and validation sets (1400 and 600 cases, respectively). Primary endpoints include sensitivity, specificity and accuracy (receiver operating characteristic curves; area under the curve value) of GAMAD for HCC and/or high-risk HCC groups. Secondary endpoints involve comparing GAMAD with the established GALAD (Gender+Age+AFP-L3+AFP+DCP) model and each blood index (AFP, DCP and methylation signature) to evaluate: (1) GAMAD's clinical utility for HCC patients in all stages according to different staging systems; (2) GAMAD's discrimination ability for patients in various subgroups, including liver cirrhosis (LC) related HCC and LC, hepatitis B virus (HBV) related HCC and HBV, hepatitis C virus (HCV) related HCC and HCV, and non-alcoholic fatty liver disease (NAFLD) related HCC and NAFLD.

ETHICS AND DISSEMINATION

This trial has been approved by the Medical Ethics Committees of the First Hospital of Jilin University (#22K073-001), the Eastern Hepatobiliary Surgery Hospital, Naval Medical University (#EHBHKY2023-H0003-P001) and Tianjin Third Central Hospital (#IRB2023-007-01). All participants in the trial will provide written informed consent. Results of this study will be disseminated in peer-reviewed scientific journals and at conferences nationally and internationally.

TRIAL REGISTRATION NUMBER

NCT05626985.

A multiplex blood-based assay targeting DNA methylation in PBMCs enables early detection of breast cancer

The immune system can monitor tumor development, and DNA methylation is involved in the body's immune response to tumors. In this work, we investigate whether DNA methylation alterations in peripheral blood mononuclear cells (PBMCs) could be used as markers for early detection of breast cancer (BC) from the perspective of tumor immune alterations. We identify four BC-specific methylation markers by combining Infinium 850 K BeadChips, pyrosequencing and targeted bisulfite sequencing. Based on the four methylation markers in PBMCs of BC, we develop an efficient and convenient multiplex methylation-specific quantitative PCR assay for the detection of BC and validate its diagnostic performance in a multicenter cohort. This assay was able to distinguish early-stage BC patients from normal controls, with an AUC of 0.940, sensitivity of 93.2%, and specificity of 90.4%. More importantly, this assay outperformed existing clinical diagnostic methods, especially in the detection of early-stage and minimal tumors.

ctDNA as a novel and promising approach for cancer diagnosis: a focus on hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most prevalent forms of cancer worldwide. Therefore, it is essential to diagnose and treat HCC patients promptly. As a novel discovery, circulating tumor DNA (ctDNA) can be used to analyze the tumor type and the cancer location. Additionally, ctDNA assists the cancer stage determination, which enables medical professionals to provide patients with the most appropriate treatment. This review will discuss the HCC-related mutated genes diagnosed by ctDNA. In addition, we will introduce the different and the most appropriate ctDNA diagnosis approaches based on the facilities.

Accurate prediction of pan-cancer types using machine learning with minimal number of DNA methylation sites

DNA methylation analysis has been applied to determine the primary site of cancer; however, robust and accurate prediction of cancer types with a minimum number of sites is still a significant scientific challenge. To build an accurate and robust cancer type prediction tool with a minimum number of DNA methylation sites, we internally benchmarked different DNA methylation site selection and ranking procedures, as well as different classification models. We used The Cancer Genome Atlas dataset (26 cancer types with 8296 samples) to train and test models and used an independent dataset (17 cancer types with 2738 samples) for model validation. A deep neural network model using a combined feature selection procedure (named MethyDeep) can predict 26 cancer types using 30 methylation sites with superior performance compared with the known methods for both primary and metastatic cancers in independent validation datasets. In conclusion, MethyDeep is an accurate and robust cancer type predictor with the minimum number of DNA methylation sites; it could help the cost-effective clarification of cancer of unknown primary patients and the liquid biopsy-based early screening of cancers.

Methylated SEPT9 combined with AFP and PIVKA-II is effective for the detection of HCC in high-risk population

BACKGROUND

The methylation SEPT9 (mSEPT9) appeared to be effective for hepatocellular carcinoma (HCC) detection. However, its performance in high-risk population has not been validated. We designed a pilot study and aimed to investigate the performance of mSEPT9, AFP, PIVKA-II and their combination in hepatic cirrhosis (HC) population.

METHODS

A training cohort was established including 103 HCC and 114 HC patients. 10 ml blood was collected from each patient with K₂EDTA tubes, and 3-4 ml plasma was extracted for subsequent tests. The performance of mSEPT9, AFP, PIVKA-II and their combination was optimized by the training cohort. Test performance was prospectively validated with a validation cohort, including 51 HCC and 121 HC patients.

RESULTS

At the optimal thresholds in the training cohort, the sensitivity, specificity and area under curve (AUC) was 72.82%, 89.47%, 0.84, and 48.57%, 89.92%, 0.79, and 63.64%, 95.95%, 0.79 for mSEPT9, AFP and PIVKA-II, respectively. The combined test significantly increased the sensitivity to 84.47% (P < 0.05) at the specificity of 86.84% with an AUC of 0.91. Stage-dependent performance was observed with all single markers and their combination in plasma marker levels, positive detection rate (PDR) and AUC. Moderate correlation was found between mSEPT9 and AFP plasma levels (r = 0.527, P < 0.0001). Good complementarity was found between any two of the three markers, providing optimal sensitivity in HCC detection when used in combination. Subsequent validation achieved a sensitivity, specificity and AUC of 65.31%, 92.86%, 0.80, and 44.24%, 89.26%, 0.75, and 62.22%, 95.27%, 0.78 for mSEPT9, AFP and PIVKA-II, respectively. The combined test yielded a significantly increased sensitivity of 84.00% (P < 0.05) at 85.57% specificity, with an AUC at 0.89.

CONCLUSIONS

The performance was optimal by the combination of mSEPT9, AFP, PIVKA-II compared with any single marker, and the combination may be effective for HCC opportunistic screening in HC population.

Genome-wide discovery of circulating cell-free DNA methylation biomarkers for colorectal cancer detection

BACKGROUND

Colorectal polyp is known a precursor of colorectal cancer (CRC) that holds an increased risk for progression to CRC. Circulating cell-free DNA (cfDNA) methylation has shown favorable performance in the detection and monitoring the malignant progression in a variety of cancers.

RESULTS

To discover cfDNA methylation markers for the diagnosis of CRC, we first performed a genome-wide analysis between eight CRC and eight polyp tissues using the Infinium HumanMethylationEPIC BeadChip. We identified 7008 DMCs, and after filtering, we validated 39 DMCs by MethylTarget sequencing in 62 CRC and 56 polyp tissues. A panel of four CpGs (cg04486886, cg06712559, cg13539460, and cg27541454) was selected as the methylation marker in tissue by LASSO and random forest models. A diagnosis prediction model was built based on the four CpGs, and the methylation diagnosis score (md-score) can effectively discriminate tissues with CRC from polyp patients (AUROC > 0.9). Finally, the cg27541454 was confirmed hypermethylated in CRC (AUC = 0.85) in the plasma validation cohort.

CONCLUSIONS

Our findings suggest that the md-score could robustly detect CRC from polyp tissues, and cg27541454 may be a promising candidate noninvasive biomarker for CRC early diagnosis.

erarchical tumor artificial intelligence classifier traces tissue of origin and tumor type in primary and metastasized tumors using DNA methylation

Human cancers are heterogenous by their cell composition and origination site. Cancer metastasis generates the conundrum of the unknown origin of migrated tumor cells. Tracing tissue of origin and tumor type in primary and metastasized cancer is vital for clinical significance. DNA methylation alterations play a crucial role in carcinogenesis and mark cell fate differentiation, thus can be used to trace tumor tissue of origin. In this study, we employed a novel tumor-type-specific hierarchical model using genome-scale DNA methylation data to develop a multilayer perceptron model, HiTAIC, to trace tissue of origin and tumor type in 27 cancers from 23 tissue sites in data from 7735 tumors with high resolution, accuracy, and specificity. In tracing primary cancer origin, HiTAIC accuracy was 99% in the test set and 93% in the external validation data set. Metastatic cancers were identified with a 96% accuracy in the external data set. HiTAIC is a user-friendly web-based application through https://sites.dartmouth.edu/salaslabhitaic/. In conclusion, we developed HiTAIC, a DNA methylation-based algorithm, to trace tumor tissue of origin in primary and metastasized cancers. The high accuracy and resolution of tumor tracing using HiTAIC holds promise for clinical assistance in identifying cancer of unknown origin.

Advances in biomarker discovery using circulating cell-free DNA for early detection of hepatocellular carcinoma

The past several decades have witnessed unprecedented progress in basic and clinical cancer research, and our understanding of the molecular mechanisms and pathogenesis of cancers have been greatly improved. More recently, with the availability of high-throughput sequencing and profiling platforms as well as sophisticated analytical tools and high-performance computing capacity, there have been tremendous advances in the development of diagnostic approaches in clinical oncology, especially the discovery of novel biomarkers for cancer early detection. Although tissue biopsy-based pathology has been the "gold standard" for cancer diagnosis, notable limitations such as the risk due to invasiveness and the bias due to intra-tumoral heterogeneity have limited its broader applications in oncology (e.g., screening, regular disease monitoring). Liquid biopsy analysis that exploits the genetic and epigenetic information contained in DNA/RNA materials from body fluids, particularly circulating cell-free DNA (cfDNA) in the blood, has been an intriguing alternative approach because of advantageous features such as sampling convenience and minimal invasiveness. Taking advantage of innovative enabling technologies, cfDNA has been demonstrated for its clinical potential in cancer early detection, including hepatocellular carcinoma (HCC), the most common liver cancer that causes serious healthcare burden globally. Hereby, we reviewed the current advances in cfDNA-based approaches for cancer biomarker discovery, with a focus on recent findings of cfDNA-based early detection of HCC. Future clinical investigations and trials are warranted to further validate these approaches for early detection of HCC, which will contribute to more effective prevention, control, and intervention strategies with the ultimate goal of reducing HCC-associated mortality. This article is categorized under: Cancer > Genetics/Genomics/Epigenetics.

Development and investigation of metabolism-associated risk assessment models for patients with viral hepatitis

Dysregulation of metabolism plays an important role in the onset and progression of multiple pathogenic diseases, including viral hepatitis. However, a model to predict viral hepatitis risk by metabolic pathways is still lacking. Thus, we developed two risk assessment models for viral hepatitis based on metabolic pathways identified through univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analysis. The first model is designed to assess the progression of the disease by evaluating changes in the Child–Pugh class, hepatic decompensation, and the development of hepatocellular carcinoma. The second model is focused on determining the prognosis of the illness, taking into account the patient’s cancer status. Our models were further validated by Kaplan–Meier plots of survival curves. In addition, we investigated the contribution of immune cells in metabolic processes and identified three distinct subsets of immune cells—CD8+ T cells, macrophages, and NK cells—that have significantly affected metabolic pathways. Specifically, our findings suggest that resting or inactive macrophages and NK cells contribute to maintaining metabolic homeostasis, particularly with regard to lipid and α-amino acid metabolism, thereby potentially reducing the risk of viral hepatitis progression. Moreover, maintaining metabolic homeostasis ensures a balance between killer-proliferative and exhausted CD8+ T cells, which helps in mitigating CD8+ T cell-mediated liver damage while preserving energy reserves. In conclusion, our study offers a useful tool for early disease detection in viral hepatitis patients through metabolic pathway analysis and sheds light on the immunological understanding of the disease through the examination of immune cell metabolic disorders.

Efficacy of ctDNA methylation combined with traditional detection modality to detect liver cancer among high-risk patients: A multicenter diagnostic trial

Objective

Circulating tumor DNA (ctDNA) and alpha-fetoprotein (AFP) plus ultrasound (US) have been considered to have high diagnostic accuracy for cancer detection, however, the efficacy of ctDNA methylation combined with the traditional detection modality of liver cancer has not been tested in a Chinese independent cohort.

Methods

The high-risk individuals aged between 35 and 70 years who were diagnosed with liver cirrhosis or had moderate and severe fatty liver were eligible for inclusion. All participants were invited to receive a traditional examination [referring to AFP plus US], and ctDNA methylation, respectively. The sensitivity and specificity of different diagnostic tools were calculated. The logistic regression model was applied to estimate the area under the curve (AUC), which was further validated by 10-fold internal cross-validation.

Results

A total of 1,205 individuals were recruited in our study, and 39 participants were diagnosed with liver cancer. The sensitivity of AFP, US, US plus AFP, and the combination of US, AFP, and ctDNA methylation was 33.33%, 56.41%, 66.67%, and 87.18%, respectively. The corresponding specificity of AFP, US, US plus AFP, and the combination of all modalities was 98.20%, 99.31%, 97.68%, and 97.68%, respectively. The AUCs of AFP, US, US plus AFP, and the combination of AFP, US, and ctDNA methylation were 65.77%, 77.86%, 82.18%, and 92.43%, respectively. The internally validated AUCs of AFP, US, US plus AFP, and the combination of AFP, US, and ctDNA methylation were 67.57%, 83.26%, 86.54%, and 93.35%, respectively.

Conclusions

The ctDNA methylation is a good complementary to AFP and US for the detection of liver cancer.

Updating the Clinical Application of Blood Biomarkers and Their Algorithms in the Diagnosis and Surveillance of Hepatocellular Carcinoma: A Critical Review

The most common primary liver cancer is hepatocellular carcinoma (HCC), and its mortality rate is increasing globally. The overall 5-year survival of patients with liver cancer is currently 10-20%. Moreover, because early diagnosis can significantly improve prognosis, which is highly correlated with tumor stage, early detection of HCC is critical. International guidelines advise using α-FP biomarker with/without ultrasonography for HCC surveillance in patients with advanced liver disease. However, traditional biomarkers are sub-optimal for risk stratification of HCC development in high-risk populations, early diagnosis, prognostication, and treatment response prediction. Since about 20% of HCCs do not produce α-FP due to its biological diversity, combining α-FP with novel biomarkers can enhance HCC detection sensitivity. There is a chance to offer promising cancer management methods in high-risk populations by utilizing HCC screening strategies derived from new tumor biomarkers and prognostic scores created by combining biomarkers with distinct clinical parameters. Despite numerous efforts to identify molecules as potential biomarkers, there is no single ideal marker in HCC. When combined with other clinical parameters, the detection of some biomarkers has higher sensitivity and specificity in comparison with a single biomarker. Therefore, newer biomarkers and models, such as the Lens culinaris agglutinin-reactive fraction of Alpha-fetoprotein (α-FP), α-FP-L3, Des-γ-carboxy-prothrombin (DCP or PIVKA-II), and the GALAD score, are being used more frequently in the diagnosis and prognosis of HCC. Notably, the GALAD algorithm was effective in HCC prevention, particularly for cirrhotic patients, regardless of the cause of their liver disease. Although the role of these biomarkers in surveillance is still being researched, they may provide a more practical alternative to traditional imaging-based surveillance. Finally, looking for new diagnostic/surveillance tools may help improve patients' survival. This review discusses the current roles of the most used biomarkers and prognostic scores that may aid in the clinical management of HCC patients.

Circulating Tumor DNA Methylation Biomarkers for Characterization and Determination of the Cancer Origin in Malignant Liver Tumors

Malignant liver tumors include primary malignant liver tumors and liver metastases. They are among the most common malignancies worldwide. The disease has a poor prognosis and poor overall survival, especially with liver metastases. Therefore, early detection and differentiation between malignant liver tumors are critical for patient treatment selection. The detection of cancer and the prediction of its origin is possible with a DNA methylation profile of the tumor DNA compared to that of normal cells, which reflects tissue differentiation and malignant transformation. New technologies enable the characterization of the tumor methylome in circulating tumor DNA (ctDNA), providing a variety of new ctDNA methylation biomarkers, which can provide additional information to clinical decision-making. Our review of the literature provides insight into methylation changes in ctDNA from patients with common malignant liver tumors and can serve as a starting point for further research.

Hepatitis Virus and Hepatocellular Carcinoma: Recent Advances

Hepatocellular carcinoma (HCC) remains a global health challenge, causing 600,000 deaths each year. Infectious factors, including hepatitis B virus (HBV), hepatitis C virus (HCV) and hepatitis D virus (HDV), have long been considered the major risk factors for the development and progression of HCC. These pathogens induce hepatocyte transformation through a variety of mechanisms, including insertional mutations caused by viral gene integration, epigenetic changes, and the induction of long-term immune dysfunction. The discovery of these mechanisms, while advancing our understanding of the disease, also provides targets for new diagnostic and therapeutic approaches. In addition, the discovery and research of chronic HEV infection over the past decade indicate that this common hepatitis virus also seems to have the potential to induce HCC. In this review, we provide an overview of recent studies on the link between hepatitis virus and HCC, as well as new diagnostic and therapeutic approaches to HCC based on these findings. Finally, we also discuss the potential relationship between HEV and HCC. In conclusion, these associations will further optimize the diagnosis and treatment of infection-associated HCC and call for better management policies.

Crosstalk between 5-methylcytosine and N6-methyladenosine machinery defines disease progression, therapeutic response and pharmacogenomic landscape in hepatocellular carcinoma

BACKGROUND

Accumulated evidence highlights the significance of the crosstalk between epigenetic and epitranscriptomic mechanisms, notably 5-methylcytosine (5mC) and N⁶-methyladenosine (m⁶A). Herein, we conducted a widespread analysis regarding the crosstalk between 5mC and m⁶A regulators in hepatocellular carcinoma (HCC).

METHODS

Pan-cancer genomic analysis of the crosstalk between 5mC and m⁶A regulators was presented at transcriptomic, genomic, epigenetic, and other multi-omics levels. Hub 5mC and m⁶A regulators were summarized to define an epigenetic and epitranscriptomic module eigengene (EME), which reflected both the pre- and post-transcriptional modifications.

RESULTS

5mC and m⁶A regulators interacted with one another at the multi-omic levels across pan-cancer, including HCC. The EME scoring system enabled to greatly optimize risk stratification and accurately predict HCC patients' clinical outcomes and progression. Additionally, the EME accurately predicted the responses to mainstream therapies (TACE and sorafenib) and immunotherapy as well as hyper-progression. In vitro, 5mC and m⁶A regulators cooperatively weakened apoptosis and facilitated proliferation, DNA damage repair, G2/M arrest, migration, invasion and epithelial-to-mesenchymal transition (EMT) in HCC cells. The EME scoring system was remarkably linked to potential extrinsic and intrinsic immune escape mechanisms, and the high EME might contribute to a reduced copy number gain/loss frequency. Finally, we determined potential therapeutic compounds and druggable targets (TUBB1 and P2RY4) for HCC patients with high EME.

CONCLUSIONS

Our findings suggest that HCC may result from a unique synergistic combination of 5mC-epigenetic mechanism mixed with m⁶A-epitranscriptomic mechanism, and their crosstalk defines therapeutic response and pharmacogenomic landscape.

Epigenetic modification-related mechanisms of hepatocellular carcinoma resistance to immune checkpoint inhibition

Hepatocellular carcinoma (HCC) constitutes most primary liver cancers and is one of the most lethal and life-threatening malignancies globally. Unfortunately, a substantial proportion of HCC patients are identified at an advanced stage that is unavailable for curative surgery. Thus, palliative therapies represented by multi-tyrosine kinase inhibitors (TKIs) sorafenib remained the front-line treatment over the past decades. Recently, the application of immune checkpoint inhibitors (ICIs), especially targeting the PD-1/PD-L1/CTLA-4 axis, has achieved an inspiring clinical breakthrough for treating unresectable solid tumors. However, many HCC patients with poor responses lead to limited benefits in clinical applications, which has quickly drawn researchers' attention to the regulatory mechanisms of immune checkpoints in HCC immune evasion. Evasion of immune surveillance by cancer is attributed to intricate reprogramming modulation in the tumor microenvironment. Currently, more and more studies have found that epigenetic modifications, such as chromatin structure remodeling, DNA methylation, histone post-translational modifications, and non-coding RNA levels, may contribute significantly to remodeling the tumor microenvironment to avoid immune clearance, affecting the efficacy of immunotherapy for HCC. This review summarizes the rapidly emerging progress of epigenetic-related changes during HCC resistance to ICIs and discusses the mechanisms of underlying epigenetic therapies available for surmounting immune resistance. Finally, we summarize the clinical advances in combining epigenetic therapies with immunotherapy, aiming to promote the formation of immune combination therapy strategies.

Methylation biomarkers for early cancer detection and diagnosis: Current and future perspectives

The increase in recent scientific studies on cancer biomarkers has brought great new insights into the field. Moreover, novel technological breakthroughs such as long read sequencing and microarrays have enabled high throughput profiling of many biomarkers, while advances in bioinformatic tools have made the possibility of developing highly reliable and accurate biomarkers a reality. These changes triggered renewed interest in biomarker research and provided tremendous opportunities for enhancing cancer management and improving early disease detection. DNA methylation alterations are known to accompany and contribute to carcinogenesis, making them promising biomarkers for cancer, namely due to their stability, frequency and accessibility in bodily fluids. The advent of newer minimally invasive experimental methods such as liquid biopsies provide the perfect setting for methylation-based biomarker development and application. Despite their huge potential, accurate and robust biomarkers for the conclusive diagnosis of most cancer types are still not routinely used, hence a strong need for sustained research in this field is still needed. This review provides a brief exposition of current methylation biomarkers for cancer diagnosis and early detection, including markers already in clinical use as well as various upcoming ones. It also outlines how recent big data and novel technologies will revolutionise the next generation of cancer tests in supplementing or replacing currently existing invasive techniques.

Tumor fractions deciphered from circulating cell-free DNA methylation for cancer early diagnosis

Tumor-derived circulating cell-free DNA (cfDNA) provides critical clues for cancer early diagnosis, yet it often suffers from low sensitivity. Here, we present a cancer early diagnosis approach using tumor fractions deciphered from circulating cfDNA methylation signatures. We show that the estimated fractions of tumor-derived cfDNA from cancer patients increase significantly as cancer progresses in two independent datasets. Employing the predicted tumor fractions, we establish a Bayesian diagnostic model in which training samples are only derived from late-stage patients and healthy individuals. When validated on early-stage patients and healthy individuals, this model exhibits a sensitivity of 86.1% for cancer early detection and an average accuracy of 76.9% for tumor localization at a specificity of 94.7%. By highlighting the potential of tumor fractions on cancer early diagnosis, our approach can be further applied to cancer screening and tumor progression monitoring.

Phosphogluconate dehydrogenase is a predictive biomarker for immunotherapy in hepatocellular carcinoma

Background

Phosphogluconate dehydrogenase (PGD) is involved in the regulation of various tumors. However, its role in hepatocellular carcinoma (HCC) is poorly understood. This study tried to determine the prognostic efficacy of PGD and its value for immunotherapy in HCC.

Methods

The data from the TCGA database was used to explore the predictive power of PGD expression and methylation on the overall survival (OS) of HCC through Cox regression and the Kaplan-Meier analysis. Then, we used the GEO and ICGC database to further verify the predictive power. Finally, the relationship between PGD and immune cells and the relationship between PGD and the efficacy of immunotherapy were explored through bioinformatics analysis in HCC.

Results

PGD is highly expressed in HCC tissues, which is negatively regulated by PGD methylation. Low PGD expression and PGD hypermethylation predict better OS in HCC patients. Besides, a meta-analysis based on the TCGA, GSE14520, and ICGC databases further confirms that low PGD expression is closely related to favorable OS. Then, we find significant differences of immune cell infiltrations between high and low PGD expression groups. Expressions of immune checkpoints, most HLA members and tumor mutation burden (TMB) are higher in the high PGD expression group, which indicates beneficial efficacy of immunotherapy in this group. And the potential mechanisms of PGD are exhibited.

Conclusion

PGD is an independent prognostic factor of HCC patients and plays an important role in immune cell infiltration and immunotherapy, which indicates that PGD can be used as a predictive biomarker for HCC immunotherapy.

Integrated machine learning methods identify FNDC3B as a potential prognostic biomarker and correlated with immune infiltrates in glioma

Background

Recent discoveries have revealed that fibronectin type III domain containing 3B (FNDC3B) acts as an oncogene in various cancers; however, its role in glioma remains unclear.

Methods

In this study, we comprehensively investigated the expression, prognostic value, and immune significance of FNDC3B in glioma using several databases and a variety of machine learning algorithms. RNA expression data and clinical information of 529 patients from the Cancer Genome Atlas (TCGA) and 1319 patients from Chinese Glioma Genome Atlas (CGGA) databases were downloaded for further investigation. To evaluate whether FNDC3B expression can predict clinical prognosis of glioma, we constructed a clinical nomogram to estimate long-term survival probabilities. The predicted nomogram was validated by CGGA cohorts. Differentially expressed genes (DEGs) were detected by the Wilcoxon test based on the TCGA-LGG dataset and the weighted gene co-expression network analysis (WGCNA) was implemented to identify the significant module associated with the expression level of FNDC3B. Furthermore, we investigated the correlation between FNDC3B with cancer immune infiltrates using TISIDB, ESTIMATE, and CIBERSORTx.

Results

Higher FNDC3B expression displayed a remarkably worse overall survival and the expression level of FNDC3B was an independent prognostic indicator for patients with glioma. Based on TCGA LGG dataset, a co-expression network was established and the hub genes were identified. FNDC3B expression was positively correlated to the tumor-infiltrating lymphocytes and immune infiltration score, and high FNDC3B expression was accompanied by the increased expression of B7-H3, PD-L1, TIM-3, PD-1, and CTLA-4. Moreover, expression of FNDC3B was significantly associated with infiltrating levels of several types of immune cells and most of their gene markers in glioma.

Conclusion

This study demonstrated that FNDC3B may be involved in the occurrence and development of glioma and can be regarded as a promising prognostic and immunotherapeutic biomarker for the treatment of glioma.

Role of 5-methylcytosine in determining the prognosis, tumor microenvironment, and applicability of precision medicine in patients with hepatocellular carcinoma

Background: 5-methylcytosine has a profound impact on the development and progression of hepatocellular carcinoma. The aim of this study was to investigate the usefulness of 5-methylcytosine in determining the prognosis, tumor microenvironment, and applicability of precision medicine in hepatocellular carcinoma.

Methods: We collected data of seven hepatocellular carcinoma cohorts (The Cancer Genome Atlas, International Cancer Genome Consortium, GSE14520, GSE6764, GSE9843, GSE63898, GSE76427). An unsupervised clustering method was used to identify novel subtypes of hepatocellular carcinoma based on the expression 5-methylcytosine gene signatures. The 5-methylcytosine score was determined using the least absolute shrinkage and selection operator method based on the differential expression of genes in the identified subtypes. Subsequently, we investigated the association between 5-methylcytosine-based clusters (according to the 5-methylcytosine score) and clinical outcomes, immunophenotypes, classical molecular subtypes, and therapeutic opportunities in hepatocellular carcinoma. Finally, we examined the sensitivity of patients with high 5-methylcytosine score to drugs.

Results: We identified two hepatocellular carcinoma-specific, 5-methylcytosine-based subtypes (clusters 1 and 2). Cluster 1 exhibited significantly higher 5-methylcytosine scores versus cluster 2. The 5-methylcytosine-based subtypes accurately predicted classical molecular subtypes, immunophenotypes, prognosis, and therapeutic opportunities for patients with hepatocellular carcinoma. Cluster 1 (high 5-methylcytosine score) was characterized by lower anticancer immunity and worse prognosis versus cluster 2 (low 5-methylcytosine score). Moreover, cluster 1 (high 5-methylcytosine score) exhibited low sensitivity to cancer immunotherapy, but high sensitivity to radiotherapy and targeted therapy with lenvatinib.

Conclusion: The novel 5-methylcytosine-based subtypes (according to the 5-methylcytosine score) may reflect the prognosis, tumor microenvironment, and applicability of precision medicine in patients with hepatocellular carcinoma.

Diagnostic and prognostic value of m5C regulatory genes in hepatocellular carcinoma

Background: A high mortality rate makes hepatocellular carcinoma (HCC) one of the most common types of cancer globally. 5-methylcytosine (m5C) is an epigenetic modification that contributes to the prognosis of several cancers, but its relevance to HCC remains unknown. We sought to determine if the m5C-related regulators had any diagnostic or prognostic value in HCC.

Methods: M5C regulatory genes were screened and compared between HCC and normal tissue from The Cancer Genome Atlas (TCGA)and Gene Expression Omnibus (GEO) databases. Least absolute shrinkage and selection operator method (LASSO) and univariate Cox regression analysis of differentially expressed genes were then performed to identify diagnostic markers. A LASSO prognostic model was constructed using M5C regulatory genes with prognostic values screened by TCGA expression data. HCC patients were stratified based on risk score, then clinical characteristics analysis and immune correlation analysis were performed for each subgroup, and the molecular functions of different subgroups were analyzed using both Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA). The prognostic model was evaluated using univariate and multivariate Cox analyses as well as a nomogram. Molecular typing was performed according to m5C regulatory genes and immune checkpoint genes expression respectively, and clinical characterization and immune correlation analysis were performed for each subgroup.

Results: M5C regulatory genes are expressed differently in HCC patients with different clinical and pathological characteristics, and mutations in these genes are frequent. Based on five m5C regulators (NOP2, NSUN2, TET1, YBX1, and DNMT3B), we constructed a prognostic model with high predictive ability. The risk score was found to be an independent prognostic indicator. Additionally, risk scores can also be applied in subgroups with different clinical characteristics as prognostic indicators.

Conclusion: The study combined data from TCGA and GEO for the first time to reveal the genetic and prognostic significance of m5C-related regulators in HCC, which provides new directions for identifying predictive biomarkers and developing molecularly targeted therapies for HCC.

DNA methylation fingerprint of hepatocellular carcinoma from tissue and liquid biopsies

Hepatocellular carcinoma (HCC) is amongst the cancers with highest mortality rates and is the most common malignancy of the liver. Early detection is vital to provide the best treatment possible and liquid biopsies combined with analysis of circulating tumour DNA methylation show great promise as a non-invasive approach for early cancer diagnosis and monitoring with low false negative rates. To identify reliable diagnostic biomarkers of early HCC, we performed a systematic analysis of multiple hepatocellular studies and datasets comprising > 1500 genome-wide DNA methylation arrays, to define a methylation signature predictive of HCC in both tissue and cell-free DNA liquid biopsy samples. Our machine learning pipeline identified differentially methylated regions in HCC, some associated with transcriptional repression of genes related with cancer progression, that benchmarked positively against independent methylation signatures. Combining our signature of 38 DNA methylation regions, we derived a HCC detection score which confirmed the utility of our approach by identifying in an independent dataset 96% of HCC tissue samples with a precision of 98%, and most importantly successfully separated cfDNA of tumour samples from healthy controls. Notably, our risk score could identify cell-free DNA samples from patients with other tumours, including colorectal cancer. Taken together, we propose a comprehensive HCC DNA methylation fingerprint and an associated risk score for detection of HCC from tissue and liquid biopsies.

Cell-free DNA as a Promising Diagnostic Biomarker in Prostate Cancer: A Systematic Review and Meta-Analysis

Objective

The detection of cell-free DNA (cfDNA) as a part of “liquid biopsy” of prostate cancer (PCa) has been widely explored. However, its diagnostic value for PCa remains controversial. Based on the data from the latest literature published in the past decade, the present review was conducted to clarify the diagnostic value of cfDNA in PCa.

Methods

The related studies were systematically searched in the databases of PubMed, Embase, Web of Science, and Cochrane Library from January 1, 2010 to December 1, 2020. Sensitivity (SEN), specificity (SPE), and other relative parameters were pooled using a random model.

Results

14 eligible studies with 1049 PCa patients and 973 controls were selected based on the inclusion and exclusion criteria. Results demonstrated that cfDNA showed favorable SPE (0.89, 95% CI: 0.79, 0.94) but unsatisfied SEN (0.56, 95% CI: 0.43, 0.68) in the PCa diagnosis. The positive likelihood ratios (PLR), negative likelihood ratios (NLR), and diagnostic odds ratios (DOR) were 5.1 (95% CI: 3.1, 8.5), 0.49 (95% CI: 0.39, 0.63), and 10 (95% CI: 6, 17), respectively. The summary receiver operating characteristic graph (SROC) with an area under the curve (AUC) of 0.80 (95% CI: 0.76, 0.83) was constructed which indicated favorable diagnostic accuracy for PCa. Results of the subgroup analysis and metaregression analysis reminded “ethnicity” and “methylation” might be sources of heterogeneity. The potential publication bias was not found using Deek's funnel plot asymmetry test (p > 0.05).

Conclusions

Our meta-analysis illustrated that the cfDNA could undertake a promising role in the PCa diagnosis.

Interferon drives HCV scarring of the epigenome and creates targetable vulnerabilities following viral clearance

BACKGROUND AND AIMS

Chronic HCV infection is a leading etiologic driver of cirrhosis and ultimately HCC. Of the approximately 71 million individuals chronically infected with HCV, 10%-20% are expected to develop severe liver complications in their lifetime. Epigenetic mechanisms including DNA methylation and histone modifications become profoundly disrupted in disease processes including liver disease.

APPROACH AND RESULTS

To understand how HCV infection influences the epigenome and whether these events remain as "scars" following cure of chronic HCV infection, we mapped genome-wide DNA methylation, four key regulatory histone modifications (H3K4me3, H3K4me1, H3K27ac, and H3K27me3), and open chromatin in parental and HCV-infected immortalized hepatocytes and the Huh7.5 HCC cell line, along with DNA methylation and gene-expression analyses following elimination of HCV in these models through treatment with interferon-α (IFN-α) or a direct-acting antiviral (DAA). Our data demonstrate that HCV infection profoundly affects the epigenome (particularly enhancers); HCV shares epigenetic targets with interferon-α targets; and an overwhelming majority of epigenetic changes induced by HCV remain as "scars" on the epigenome following viral cure. Similar findings are observed in primary human patient samples cured of chronic HCV infection. Supplementation of IFN-α/DAA antiviral regimens with DNA methyltransferase inhibitor 5-aza-2'-deoxycytidine synergizes in reverting aberrant DNA methylation induced by HCV. Finally, both HCV-infected and cured cells displayed a blunted immune response, demonstrating a functional effect of epigenetic scarring.

CONCLUSIONS

Integration of epigenetic and transcriptional data elucidate key gene deregulation events driven by HCV infection and how this may underpin the long-term elevated risk for HCC in patients cured of HCV due to epigenome scarring.

Comprehensive Analysis of DNA 5-Methylcytosine and N6-Adenine Methylation by Nanopore Sequencing in Hepatocellular Carcinoma

DNA methylation is a widespread epigenetic signal in human genome. With Nanopore technology, differential methylation modifications including 5-methylcytosine (5mC) and 6-methyladenine (6mA) can be identified. 5mC is the most important modification in mammals, although 6mA may also function in growth and development as well as in pathogenesis. While the role of 5mC at CpG islands in promoter regions associated with transcriptional regulation has been well studied, but the relationship between 6mA and transcription is still unclear. Thus, we collected two pairs of tumor tissues and adjacent normal tissues from hepatocellular carcinoma (HCC) surgical samples for Nanopore sequencing and transcriptome sequencing. It was found that 2,373 genes had both 5mC and 6mA, along with up- and down-regulated methylation sites. These genes were regarded as unstable methylation genes. Compared with 6mA, 5mC had more inclined distribution of unstable methylation sites. Chi-square test showed that the levels of 5mC were consistent with both up- and down-regulated genes, but 6mA was not significant. Moreover, the top three unstable methylation genes, TBC1D3H, CSMD1, and ROBO2, were all related to cancer. Transcriptome and survival analyses revealed four potential tumor suppressor genes including KCNIP4, CACNA1C, PACRG, and ST6GALNAC3. In this study, we firstly proposed to combine 5mC and 6mA methylation sites to explore functional genes, and further research found top of these unstable methylation genes might be functional and some of them could serve as potential tumor suppressor genes. Our study provided a new solution for epigenetic regulation research and therapy of HCC.

MicroRNA expression is deregulated by aberrant methylation in B-cell acute lymphoblastic leukemia mouse model

BACKGROUND

The expression of microRNAs (miRNAs) in the serum of B-cell acute lymphoblastic leukemia (B-ALL) patients is abnormal. Nevertheless, the underlying mechanism remains unclear. Recent studies indicate that the methylation state of circulating cell-free DNA (cfDNA) is different between cancer patients and healthy individuals. Therefore, we speculate that abnormal expression of miRNA may be associated with cfDNA methylation.

METHODS

A green fluorescent protein (GFP) labeled B-ALL transplantation animal model was established to explore the relationship between the miRNA expression and cfDNA methylation of the related gene. Quantitative real-time PCR (qRT-PCR) was used to detect the expression levels of miRNAs. Further, cfDNA methylation levels of the related genes were evaluated through bisulfite sequencing polymerase chain reaction (BSP).

RESULTS

The expression levels of miR-196b, miR-203, miR-34a-5p, miR-335-3p, miR-34b-5p, miR-615, miR-375-3p and miR-193b-5p in the serum of the model mice were significantly lower than those of the control group (P < 0.05). The methylation level of miR-196b promoter in cfDNA of the model group was significantly lower than that of the control group (P < 0.05), whereas no significant difference was noted in miR-203 promoter. The methylation levels of miR-196b and miR-203 coding region in cfDNA of the model group were significantly higher than those of the control group (P < 0.05).

CONCLUSIONS

These results showed that CpG island hypermethylation in the miRNA coding region of cfDNA is related to the low expression of miR-196b and miR-203.

A Sight of the Diagnostic Value of Aberrant Cell-Free DNA Methylation in Lung Cancer

Background

Lung cancer is one of the most commonly diagnosed cancer worldwide. As one of the liquid biopsy analytes, alternations in cell-free DNA (cfDNA) methylation could function as promising biomarkers for lung cancer detection.

Methods

In this study, differential methylation analysis was performed to identify candidate markers, and lasso regression with 10-fold cross-validation (CV) was used to establish the diagnostic marker panel. The performance of the binary classifier was evaluated using the receiver operating characteristic (ROC) curve and the precision-recall (PR) curve.

Results

We identified 4072 differentially methylated regions (DMRs) based on cfDNA methylation data, and then a 10-DMR marker panel was established. The panel achieved an area under the ROC curve (AUROC) of 0.922 and an area under the PR curve (AUPR) of 0.899 in a cfDNA cohort containing 29 lung cancer and 74 normal samples, showing outstanding performance. Besides, the cfDNA-derived markers also performed well in primary tissue datasets, which were more robust than the tissue-derived markers.

Conclusion

Our study suggested that the 10-DMR marker panel attained high accuracy and robustness and may function as a novel and promising target for lung cancer detection.

A convergent synthetic platform for dual anticancer drugs functionalized by reduced graphene nanocomposite delivery for hepatocellular cancer

Hepatocellular carcinoma (HCC) is widespread cancer with a high degree of morbidity and mortality in individuals worldwide and a serious concern for its resistance to present chemotherapy drugs. In this investigation, the combination of cisplatin (CPT) and metformin (MET) to kill the HepG2 and caco-2 cells was developed into a new pH-responding magnetic nanocomposite based on reduced graphene oxide. Polyhydroxyethyl methacrylic (PHEA) was then linked employing grafting from approach to the reduced graphene oxide by ATRP polymerization (Fe₃O₄@rGO-G-PSEA). FT-IR, SEM, XRD, DLS, and TGA analyses evaluated physicochemical characteristics of the nanocomposite. In addition, the cellular uptake property of the nanocomposites was examined by the HepG2 cells. The outcomes of cell viability results indicate that the nanoparticles loaded with MET&CPT showed the lowest concentration rate of HepG2 and Caco-2 cells compared to the drug-loaded single nanocomposite groups and free drugs. The histological analysis has demonstrated relatively safe and does not produce different stress such as swelling and inflammation of the mice organs. Our results show the enhancement in cytotoxicity in HepG2 and Cocoa-2 cells by MET and CPT graphene oxide-based nanocomposite by promoting apoptotic response. Moreover, Fe₃O₄@rGO-G-PSEA showed potent in vivo antitumor efficacy but showed no adverse toxicity to normal tissues. Together, this study can provide insight into how surface embellishment may tune these nanocomposites' tumor specificity and provide the basis for developing anticancer efficacy.

Role of Circulating Tumor DNA in Gastrointestinal Cancers: Current Knowledge and Perspectives

Gastrointestinal (GI) cancers are major health burdens worldwide and biomarkers are needed to improve the management of these diseases along their evolution. Circulating tumor DNA (ctDNA) is a promising non-invasive blood and other bodily-fluid-based biomarker in cancer management that can help clinicians in various cases for the detection, diagnosis, prognosis, monitoring and personalization of treatment in digestive oncology. In addition to the well-studied prognostic role of ctDNA, the main real-world applications appear to be the assessment of minimal residual disease to further guide adjuvant therapy and predict relapse, but also the monitoring of clonal evolution to tailor treatments in metastatic setting. Other challenges such as predicting response to treatment including immune checkpoint inhibitors could also be among the potential applications of ctDNA. Although the level of advancement of ctDNA development in the different tumor localizations is still inhomogeneous, it might be now reliable enough to be soon used in clinical routine for colorectal cancers and shows promising results in other GI cancers.

Multi-Omic Analyses of the m5C Regulator ALYREF Reveal Its Essential Roles in Hepatocellular Carcinoma

The ALYREF protein acts as a crucial epigenetic regulator in several cancers. However, the specific expression levels and functional roles of ALYREF in cancers are largely unknown, including for hepatocellular carcinoma (HCC). In a pan-cancer tissue analysis that included HCC, we assessed the expression of ALYREF compared to normal tissues using The Cancer Genome Atlas database. Associations between ALYREF gene expression and the clinical characteristics of HCC patient samples were assessed using the UALCAN database. Kaplan-Meier plots were performed to assess HCC patient prognosis, and the TIMER database was used to explore associations between ALYREF expression and immune-cell infiltrations. The same methods were used to assess eIF4A3 expression in HCC patient samples. In addition, ALYREF- and elF4A3-related differentially expressed genes (DEGs) were determined using LinkedOmics, associated protein functionalities were predicted for positively associated DEGs, and both the TargetScan and miRDB databases were used to predict potential upstream miRNAs for control of ALYREF and eIF4A3 expression. We found that ALYREF gene expression was dysregulated in several cancers and was significantly elevated in HCC patient tissue samples and HCC cell lines. The overexpression of ALYREF was significantly related to both advanced tumor-node-metastasis stages and poor HCC prognosis. Furthermore, we found that eIF4A3 expression was significantly correlated with ALYREF expression, and that upregulated eIF4A3 was significantly associated with poor HCC patient outcomes. In the protein-protein interaction network, we identified eight hub genes based on the positively associated DEGs in common between ALYREF and eIF4A3, and the high expression levels of these hub genes were positively associated with patient clinical outcomes. In addition, we identified miR-4666a-5p and miR-6124 as potential regulators of ALYREF and eIF4A3 expression. These findings suggest that increased ALYREF expression may function as a novel biomarker for both HCC diagnosis and prognosis predictions.

Characterization of fragment sizes, copy number aberrations and 4-mer end motifs in cell-free DNA of hepatocellular carcinoma for enhanced liquid biopsy-based cancer detection

Circulating cell‐free DNA (cfDNA) fragmentomics, which encompasses the measurement of cfDNA length and short nucleotide motifs at the ends of cfDNA molecules, is an emerging field for cancer diagnosis. The utilization of cfDNA fragmentomics for the diagnosis of patients with hepatocellular carcinoma (HCC) caused by hepatitis B virus (HBV) is currently limited. In this study, we utilized whole‐genome sequencing data of cfDNA in samples from patients with HCC (n = 197) and HBV (n = 187) to analyze the association of fragment size selection (< 150 bp) with tumor fraction (TF), copy number variation (CNV) alterations and the change in the proportion of 4‐mer end motifs in HCC and HBV samples. Our analyses identified five typical CNV markers (i.e. loss in chr1p, chr4q and chr8p, and gain in chr1q and chr8q) in cfDNA with a cumulatively positive rate of ˜ 95% in HCC samples. Size selection (< 150 bp) significantly enhanced TF and CNV signals in HCC samples. Additionally, three 4‐mer end motifs (CCCA, CCTG and CCAG) were identified as preferred end motifs in HCC samples. We identified 139 end motifs significantly associated with fragment size that showed similar patterns of associations between patients with HCC and HBV, suggesting that end motifs might be inherently coupled with fragment size by a ubiquitous mechanism. Here we conclude that CNV markers, fragment size selection and end‐motif pattern in cfDNA have potential for effective detection of patients with HCC.

A Novel Post-Operative ALRI Model Accurately Predicts Clinical Outcomes of Resected Hepatocellular Carcinoma Patients

Background

Hepatocellular carcinoma (HCC) is one of the leading malignant tumors worldwide. Prognosis and long-term survival of HCC remain unsatisfactory, even after radical resection, and many non-invasive predictors have been explored for post-operative patients. Most prognostic prediction models were based on preoperative clinical characteristics and pathological findings. This study aimed to investigate the prognostic value of a newly constructed nomogram, which incorporated post-operative aspartate aminotransferase to lymphocyte ratio index (ALRI).

Methods

A total of 771 HCC patients underwent radical resection from three medical centers were enrolled and grouped into the training cohort (n = 416) and validation cohort (n = 355). Prognostic prediction potential of ALRI was assessed by receiver operating curve (ROC) analysis. The Cox regression model was used to identify independent prognostic factors. Nomograms for overall survival (OS) and disease-free survival (DFS) were constructed and further validated externally.

Results

The ROC analysis ranked ALRI as the most effective prediction marker for resected HCC patients, with the cut-off value determined at 22.6. Higher ALRI level positively correlated with larger tumor size, higher tumor node metastasis (TNM) stage, and inversely with lower albumin level and shorter OS and DFS. Nomograms for OS and DFS were capable of discriminating HCC patients into different risk-groups.

Conclusions

Post-operative ALRI was of prediction value for HCC prognosis. This novel nomogram may categorize HCC patients into different risk groups, and offer individualized surveillance reference for post-operative patients.

Screening the genome for HCC-specific CpG methylation signatures as biomarkers for diagnosis and prognosis evaluation

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most common and invasive malignant tumors in the world. The change in DNA methylation is a key event in HCC.

METHODS

Methylation datasets for HCC and 17 other types of cancer were downloaded from The Cancer Genome Atlas (TCGA). The CpG sites with large differences in methylation between tumor tissues and paracancerous tissues were identified. We used the HCC methylation dataset downloaded from the TCGA as the training set and removed the overlapping sites among all cancer datasets to ensure that only CpG sites specific to HCC remained. Logistic regression analysis was performed to select specific biomarkers that can be used to diagnose HCC, and two datasets-GSE157341 and GSE54503-downloaded from GEO as validation sets were used to validate our model. We also used a Cox regression model to select CpG sites related to patient prognosis.

RESULTS

We identified 6 HCC-specific methylated CpG sites as biomarkers for HCC diagnosis. In the training set, the area under the receiver operating characteristic (ROC) curve (AUC) for the model containing all these sites was 0.971. The AUCs were 0.8802 and 0.9711 for the two validation sets from the GEO database. In addition, 3 other CpG sites were analyzed and used to create a risk scoring model for patient prognosis and survival prediction.

CONCLUSIONS

Through the analysis of HCC methylation datasets from the TCGA and Gene Expression Omnibus (GEO) databases, potential biomarkers for HCC diagnosis and prognosis evaluation were ascertained.

The Landscape of Cell-Free HBV Integrations and Mutations in Cirrhosis and Hepatocellular Carcinoma Patients

PURPOSE

Intratumoral hepatitis B virus (HBV) integrations and mutations are related to hepatocellular carcinoma (HCC) progression. Circulating cell-free DNA (cfDNA) has shown itself as a powerful noninvasive biomarker for cancer. However, the HBV integration and mutation landscape on cfDNA remains unclear.

EXPERIMENTAL DESIGN

A cSMART (Circulating Single-Molecule Amplification and Resequencing Technology)-based method (SIM) was developed to simultaneously investigate HBV integration and mutation landscapes on cfDNA with HBV-specific primers covering the whole HBV genome. Patients with HCC (n = 481) and liver cirrhosis (LC; n = 517) were recruited in the study.

RESULTS

A total of 6,861 integration breakpoints including TERT and KMT2B were discovered in HCC cfDNA, more than in LC. The concentration of circulating tumor DNA (ctDNA) was positively correlated with the detection rate of these integration hotspots and total HBV integration events in cfDNA. To track the origin of HBV integrations in cfDNA, whole-genome sequencing (WGS) was performed on their paired tumor tissues. The paired comparison of WGS data from tumor tissues and SIM data from cfDNA confirmed most recurrent integration events in cfDNA originated from tumor tissue. The mutational landscape across the whole HBV genome was first generated for both HBV genotype C and B. A region from nt1100 to nt1500 containing multiple HCC risk mutation sites (OR > 1) was identified as a potential HCC-related mutational hot zone.

CONCLUSIONS

Our study provides an in-depth delineation of HBV integration/mutation landscapes at cfDNA level and did a comparative analysis with their paired tissues. These findings shed light on the possibilities of noninvasive detection of virus insertion/mutation.

Current status of ctDNA in precision oncology for hepatocellular carcinoma

The conventional method used to obtain a tumor biopsy for hepatocellular carcinoma (HCC) is invasive and does not evaluate dynamic cancer progression or assess tumor heterogeneity. It is thus imperative to create a novel non-invasive diagnostic technique for improvement in cancer screening, diagnosis, treatment selection, response assessment, and predicting prognosis for HCC. Circulating tumor DNA (ctDNA) is a non-invasive liquid biopsy method that reveals cancer-specific genetic and epigenetic aberrations. Owing to the development of technology in next-generation sequencing and PCR-based assays, the detection and quantification of ctDNA have greatly improved. In this publication, we provide an overview of current technologies used to detect ctDNA, the ctDNA markers utilized, and recent advances regarding the multiple clinical applications in the field of precision medicine for HCC.

Evaluation of circulating cell-free DNA in cholestatic liver disease using liver-specific methylation markers

Background

Quantification of circulating organ-specific cell-free DNA (cfDNA) provides a sensitive measure of ongoing cell death that could benefit evaluation of the cholestatic liver diseases primary biliary cholangitis (PBC) and primary sclerosing cholangitis (PSC), which lack reliable non-invasive biomarkers. Our goal in this pilot study was to determine whether liver-specific cfDNA levels are increased in PBC and PSC patients relative to controls and in advanced versus early disease, to evaluate their potential as novel disease biomarkers.

Methods

Peripheral blood derived bisulfite-treated DNA was PCR amplified from patients with PBC (n = 48), PSC (n = 48) and controls (n = 96) to evaluate methylation status at 16 CpG sites reported to be specifically unmethylated in liver tissue near the genes IGF2R, ITIH4 and VTN. Amplicons were used to prepare paired end libraries which were sequenced on a MiSeq sequencer. Trimmed reads were aligned and used to determine unmethylation ratios and to calculate concentration of liver-specific cfDNA. Comparisons between groups were performed using the two-tailed Mann–Whitney Test and relationships between variables were evaluated using Pearson’s Correlation.

Results

Levels of liver-specific cfDNA, as measured at the 3 genetic loci, were increased in PBC and PSC patients relative to controls and in late-stage relative to early-stage patients. As well, cfDNA levels were correlated with levels of alkaline phosphatase, a commonly used biochemical test to evaluate disease severity in liver disease, in patients, but not in controls.

Conclusions

cfDNA offers promise as a non-invasive liquid-biopsy to evaluate liver-specific cell-death in patients with cholestatic liver diseases.

Plasma cell free DNA methylation markers for hepatocellular carcinoma surveillance in patients with cirrhosis: a case control study

BACKGROUND

Hepatocellular carcinoma (HCC) is the leading cause of death in patients with cirrhosis, primarily due to failed early detection. HCC screening is recommended among individuals with cirrhosis using biannual abdominal ultrasound, for earlier tumor detection, administration of curative treatment, and improved survival. Surveillance by imaging with or without biomarkers such as alpha-fetoprotein (AFP) remains suboptimal for early stage HCC detection. Here we report on the development and assessment of methylation biomarkers from liquid biopsies for HCC surveillance in cirrhotic patients.

METHODS

DNA methylation markers including the HCCBloodTest (Epigenomics AG) and a DNA-methylation panel established by next generation sequencing (NGS) were assessed using a training/testing design. The NGS panel algorithm was established in a training study (41 HCC patients; 46 cirrhotic non-HCC controls). For testing, plasma samples were obtained from cirrhotic patients (Child class A or B) with (60) or without (103) early stage HCC (BCLC stage 0, A, B). The assays were then tested using blinded sample sets and analyzed by preset algorithms.

RESULTS

The HCCBloodTest and the NGS panel exhibited 76.7% and 57% sensitivities at 64.1% and 97% specificity, respectively. In a post-hoc analysis, a combination of the NGS panel with AFP (20 ng/mL) achieved 68% sensitivity at 97% specificity (AUC = 0.9).

CONCLUSIONS

Methylation biomarkers in cell free plasma DNA provide a new alternative for HCC surveillance. Multiomic panels comprising DNA methylation markers with other biological markers, such as AFP, provide an option to further increase the overall clinical performance of surveillance via minimally invasive blood samples.

TRIAL REGISTRATION

Test set study-ClinicalTrials.gov (NCT03804593) January 11, 2019, retrospectively registered.

Epigenetic Biomarkers for the Diagnosis and Treatment of Liver Disease

Research in the last decades has demonstrated the relevance of epigenetics in controlling gene expression to maintain cell homeostasis, and the important role played by epigenome alterations in disease development. Moreover, the reversibility of epigenetic marks can be harnessed as a therapeutic strategy, and epigenetic marks can be used as diagnosis biomarkers. Epigenetic alterations in DNA methylation, histone post-translational modifications (PTMs), and non-coding RNA (ncRNA) expression have been associated with the process of hepatocarcinogenesis. Here, we summarize epigenetic alterations involved in the pathogenesis of chronic liver disease (CLD), particularly focusing on DNA methylation. We also discuss their utility as epigenetic biomarkers in liquid biopsy for the diagnosis and prognosis of hepatocellular carcinoma (HCC). Finally, we discuss the potential of epigenetic therapeutic strategies for HCC treatment.

An integrated epigenomic-transcriptomic landscape of lung cancer reveals novel methylation driver genes of diagnostic and therapeutic relevance

Background: Aberrant DNA methylation occurs commonly during carcinogenesis and is of clinical value in human cancers. However, knowledge of the impact of DNA methylation changes on lung carcinogenesis and progression remains limited.

Methods: Genome-wide DNA methylation profiles were surveyed in 18 pairs of tumors and adjacent normal tissues from non-small cell lung cancer (NSCLC) patients using Reduced Representation Bisulfite Sequencing (RRBS). An integrated epigenomic-transcriptomic landscape of lung cancer was depicted using the multi-omics data integration method.

Results: We discovered a large number of hypermethylation events pre-marked by poised promoter in embryonic stem cells, being a hallmark of lung cancer. These hypermethylation events showed a high conservation across cancer types. Eight novel driver genes with aberrant methylation (e.g., PCDH17 and IRX1) were identified by integrated analysis of DNA methylome and transcriptome data. Methylation level of the eight genes measured by pyrosequencing can distinguish NSCLC patients from lung tissues with high sensitivity and specificity in an independent cohort. Their tumor-suppressive roles were further experimentally validated in lung cancer cells, which depend on promoter hypermethylation. Similarly, 13 methylation-driven ncRNAs (including 8 lncRNAs and 5 miRNAs) were identified, some of which were co-regulated with their host genes by the same promoter hypermethylation. Finally, by analyzing the transcription factor (TF) binding motifs, we uncovered sets of TFs driving the expression of epigenetically regulated genes and highlighted the epigenetic regulation of gene expression of TCF21 through DNA methylation of EGR1 binding motifs.

Conclusions: We discovered several novel methylation driver genes of diagnostic and therapeutic relevance in lung cancer. Our findings revealed that DNA methylation in TF binding motifs regulates target gene expression by affecting the binding ability of TFs. Our study also provides a valuable epigenetic resource for identifying DNA methylation-based diagnostic biomarkers, developing cancer drugs for epigenetic therapy and studying cancer pathogenesis.

Endogenous retrovirus expression activates type-I interferon signaling in an experimental mouse model of mesothelioma development

Early events in an experimental model of mesothelioma development include increased levels of editing in double-stranded RNA (dsRNA). We hypothesised that expression of endogenous retroviruses (ERV) contributes to dsRNA formation and type-I interferon signaling. ERV and interferon stimulated genes (ISGs) expression were significantly higher in tumor compared to non-tumor samples. 12 tumor specific ERV ("MesoERV1-12") were identified and verified by qPCR in mouse tissues. "MesoERV1-12" expression was lower in mouse embryonic fibroblasts (MEF) compared to mesothelioma cells. "MesoERV1-12" levels were significantly increased by demethylating agent 5-Aza-2'-deoxycytidine treatment and were accompanied by increased levels of dsRNA and ISGs. Basal ISGs expression was higher in mesothelioma cells compared to MEF and was significantly decreased by JAK inhibitor Ruxolitinib, by blocking Ifnar1 and by silencing Mavs. "MesoERV7" promoter was demethylated in asbestos-exposed compared to sham mice tissue as well as in mesothelioma cells and MEF upon 5-Aza-CdR treatment. These observations uncover novel aspects of asbestos-induced mesothelioma whereby ERV expression increases due to promoter demethylation and is paralleled by increased levels of dsRNA and activation of type-I IFN signaling. These features are important for early diagnosis and therapy.

JKAMP inhibits the osteogenic capacity of adipose-derived stem cells in diabetic osteoporosis by modulating the Wnt signaling pathway through intragenic DNA methylation

Background

Diabetic osteoporosis (DOP) is a systemic metabolic bone disease caused by diabetes mellitus (DM). Adipose-derived stem cells (ASCs) play an important role in bone regeneration. Our previous study confirmed that ASCs from DOP mice (DOP-ASCs) have a lower osteogenesis potential compared with control ASCs (CON-ASCs). However, the cause of this poor osteogenesis has not been elucidated. Therefore, this study investigated the underlying mechanism of the decline in the osteogenic potential of DOP-ASCs from the perspective of epigenetics and explored methods to enhance their osteogenic capacity.

Methods

The expression level of JNK1-associated membrane protein (JKAMP) and degree of DNA methylation in CON-ASCs and DOP-ASCs were measured by mRNA expression profiling and MeDIP sequencing, respectively. JKAMP small interfering RNA (siRNA) and a Jkamp overexpression plasmid were used to assess the role of JKAMP in osteogenic differentiation of CON-ASCs and DOP-ASCs. Immunofluorescence, qPCR, and western blotting were used to measure changes in expression of Wnt signaling pathway-related genes and osteogenesis-related molecules after osteogenesis induction. Alizarin red and ALP staining was used to confirm the osteogenic potential of stem cells. Bisulfite-specific PCR (BSP) was used to detect JKAMP methylation degree.

Results

Expression of JKAMP and osteogenesis-related molecules (RUNX2 and OPN) in DOP-ASCs was decreased significantly in comparison with CON-ASCs. JKAMP silencing inhibited the Wnt signaling pathway and reduced the osteogenic ability of CON-ASCs. Overexpression of JKAMP in DOP-ASCs rescued the impaired osteogenic capacity caused by DOP. Moreover, JKAMP in DOP-ASCs contained intragenic DNA hypermethylated regions related to the downregulation of JKAMP expression.

Conclusions

Intragenic DNA methylation inhibits the osteogenic ability of DOP-ASCs by suppressing expression of JKAMP and the Wnt signaling pathway. This study shows an epigenetic explanation for the reduced osteogenic ability of DOP-ASCs and provides a potential therapeutic target to prevent and treat osteoporosis.

Identification of DNA methylation signatures associated with poor outcome in lower-risk Stage, Size, Grade and Necrosis (SSIGN) score clear cell renal cell cancer

BACKGROUND

Despite using prognostic algorithms and standard surveillance guidelines, 17% of patients initially diagnosed with low risk clear cell renal cell carcinoma (ccRCC) ultimately relapse and die of recurrent disease, indicating additional molecular parameters are needed for improved prognosis.

RESULTS

To address the gap in ccRCC prognostication in the lower risk population, we performed a genome-wide analysis for methylation signatures capable of distinguishing recurrent and non-recurrent ccRCCs within the subgroup classified as 'low risk' by the Mayo Clinic Stage, Size, Grade, and Necrosis score (SSIGN 0-3). This approach revealed that recurrent patients have globally hypermethylated tumors and differ in methylation significantly at 5929 CpGs. Differentially methylated CpGs (DMCpGs) were enriched in regulatory regions and genes modulating cell growth and invasion. A subset of DMCpGs stratified low SSIGN groups into high and low risk of recurrence in independent data sets, indicating that DNA methylation enhances the prognostic power of the SSIGN score.

CONCLUSIONS

This study reports a global DNA hypermethylation in tumors of recurrent ccRCC patients. Furthermore, DMCpGs were capable of discriminating between aggressive and less aggressive tumors, in addition to SSIGN score. Therefore, DNA methylation presents itself as a potentially strong biomarker to further improve prognostic power in patients with low risk SSIGN score (0-3).

Utilization of circulating cell-free DNA profiling to guide first-line chemotherapy in advanced lung squamous cell carcinoma

Rationale: Platinum-based chemotherapy is one of treatment mainstay for patients with advanced lung squamous cell carcinoma (LUSC) but it is still a "one-size fits all" approach. Here, we aimed to investigate the predictive and monitoring role of circulating cell-free DNA (cfDNA) profiling for the outcome of first-line chemotherapy in patients with advanced LUSC. Methods: Peripheral blood samples of 155 patients from a phase IV trial and 42 cases from an external real-world cohort were prospectively collected. We generated a copy number variations-based classifier via machine learning algorithm to integrate molecular profiling of cfDNA, named RESPONSE SCORE (RS) to predict the treatment outcome. To monitor the treatment efficacy, cfDNA samples collected at different time points were subjected to an ultra-deep sequencing platform. Results: The results showed that patients with high RS showed substantially higher objective response rate than those with low RS in training set (P < 0.001), validation set (P < 0.001) and real-world cohort (P = 0.019). Furthermore, a significant difference was observed in both progression-free survival (training set, P < 0.001; validation set: P < 0.001; real-world cohort: P = 0.019) and overall survival (training set, P < 0.001; validation set: P = 0.037) between high and low RS group. Notably, variant allele frequency (VAF) calculated from an ultra-deep sequencing platform significantly reduced in patients experienced a complete or partial response after 2 cycles of chemotherapy (P < 0.001), while it significantly increased in these of non-responder (P < 0.001). Moreover, VAF undetectable after 2 cycles of chemotherapy was correlated with markedly better objective response rate (P < 0.001) and progression-free survival (P < 0.001) than those with detectable VAF. Conclusions: These findings indicated that the RS, a circulating cfDNA sequencing-based stratification index, could help to guide first-line chemotherapy in advanced LUSC. The change of VAF is valuable to monitor the treatment response.

Novel Molecular Subtypes Associated With 5mC Methylation and Their Role in Hepatocellular Carcinoma Immunotherapy

Background

5-methylcytosine (5mC) has been reported in the prognosis of a variety of cancers, however, its role in hepatocellular carcinoma (HCC) has not been investigated yet. This study aimed at identifying the molecular subtypes associated with 5mC and establishing a relevant score to predict its prognosis in HCC.

Methods

Somatic gene mutation data and gene expression data were retrieved from The Cancer Genome Atlas database. Molecular subtypes were identified by unsupervised clustering based on the expression of 5mC regulators, and the molecular features of each subtype were investigated by survival, mutation, gene set variation, and immune cell infiltration analyses. Next, we performed a differentially expressed analysis based on the new subtypes and selected the overlapping genes for further analysis. We undertook univariate Cox analysis to analyze these genes and constructed a prognostic model by lasso regression analysis. Meanwhile, survival and gene set enrichment analyses were used to explore the prognosis and the relevant pathways, respectively. The LIRI cohort from the International Cancer Genome Consortium database was used as a reference to validate the 5mC subtypes and 5mC score.

Results

Twenty-one types of 5mC regulators were employed in this study, and three 5mC-associated molecular subtypes were identified. These three subtypes presented significant differences in prognosis, immune cell infiltration, immune checkpoint inhibitors, signaling pathways, and mutational features. Compared with cluster 3, cluster 2 exhibited significantly increased expression of PD-L1, TIM3, Galectin9, CTLA4, and CD80, while PD-L1, TIM3, and CD80 were higher in cluster 2 than in cluster 1. Furthermore, a 5mC-related score, composed of seven genes (SGPP2, SALL4, B3GNT7, ROR1, MYBL2, SLC7A1, and CAND2), was proven to be significantly associated with prognosis. The established subtypes and scores were thus successfully verified by the validated cohort.

Conclusion

To the best of our knowledge, this is the first study to identify a novel molecular subtype based on 5mC regulators. The identification of the 5mC-associated subtype may help reveal the potential relation between 5mC and immunity and provide novel insights for the development of individualized therapy for HCC.

Molecular tumor classification using DNA methylome analysis

Tumor classifiers based on molecular patterns promise to define and reliably classify tumor entities. The high tissue- and cell type-specificity of DNA methylation, as well as its high stability, makes DNA methylation an ideal choice for the development of tumor classifiers. Herein, we review existing tumor classifiers using DNA methylome analysis and will provide an overview on their emerging impact on cancer classification, the detection of novel cancer subentities and patient stratification with a focus on brain tumors, sarcomas and hematopoietic malignancies. Furthermore, we provide an outlook on the enormous potential of DNA methylome analysis to complement classical histopathological and genetic diagnostics, including the emerging field of epigenomic analysis in liquid biopsies.

The use of minimally invasive biomarkers for the diagnosis and prognosis of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a common cause of cancer-related deaths worldwide. Despite advances in systemic therapies, patient survival remains low due to late diagnosis and frequent underlying liver diseases. HCC diagnosis generally relies on imaging and liver tissue biopsy. Liver biopsy presents limitations because it is invasive, potentially risky for patients and it frequently misrepresents tumour heterogeneity. Recently, liquid biopsy has emerged as a way to monitor cancer progression in a non-invasive manner. Tumours shed content into the bloodstream, such as circulating tumour cells (CTCs), circulating nucleic acids, extracellular vesicles and proteins, that can be isolated from biological fluids of patients with HCC. These biomarkers provide knowledge regarding the genetic landscape of tumours and might be used for diagnostic or prognostic purposes. In this review, we summarize recent literature on circulating biomarkers for HCC, namely CTCs, circulating tumour DNA (ctDNA), RNA, extracellular vesicles and proteins, and their clinical relevance in HCC.